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|Title:||Biocybernetic closed-loop system to improve engagement in video games using electroencephalography|
|Keywords:||EEG,;DDA,;video games,;engagement,;flow;BCI;HCI;behavioral sciences;Unity;Python;C#|
|Abstract:||The purpose of this paper was to determine the level of engagement with a specific stimuli while playing video games. The modern video game industry has a large and wide audience and is therefore becoming more popular and accessible to the public. The interactions and rewards offered in video games are a key to keep player engagement high. Understanding the player’s brain and how it reacts to different type of stimuli would help to continue improving games and advance the industry into a new era. Although studying human engagement had started many years ago, the application of measuring it in video game players has only been applied more recently and is still an evolving field of research. This thesis will be taking an objective approach by measuring engagement through electroencephalogram (EEG) readings and seeing if it will help improve current dynamic difficulty adjustment (DDA) systems for video games leading to more engaging and entertaining games. Although statistically significant findings were not found in this experiment, the technique for future experiments were laid out in the form of classifiers comparison and program layouts.|
|Appears in Collections:||Computational Sciences - Master's theses|
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